Entropy filter, and area extracting method using the filter

ABSTRACT

A smooth portion is efficiently extracted from an image. There is provided an entropy filter in which a noted pixel (x, y) is determined in an original image, said image is partitioned by a window of size (width, height)=(A, B) from the noted pixel, entropy of the partitioned window is calculated, and obtained entropy value is saved on the coordinates (x, y) of a resulting image. Here, in a noted pixel (x, y), x is ranged from 0 to (an image width minus a window width) and y is ranged from 0 to (an image height minus a window height). By using an entropy filter, a smooth portion in image quality is extracted from an original image. A preferred example of the smooth portion is a cell nucleus.

FIELD OF THE INVENTION

The present invention relates to a filter for extracting a smooth areain image quality or coarse area in image quality from an image, and toan area extracting method for efficiently extracting a smooth area inimage quality or coarse area in image quality from an image. In thespecification, the present invention will be explained on a nucleusextraction from a cell image taken by a Nomarski DIC microscope(hereafter referred to as a “Nomarski microscope”) as a preferredexample. The technique employed by the present invention is not limitedto an image taken by the Nomarski microscope nor a nucleus extractionfrom a cell image but can widely be applied to a feature extraction froman image and image recognition.

BACKGROUND OF THE INVENTION

There is an occasion to extract a nucleus area from a cell image.Specifically, it is important to efficiently recognize a nucleus areafrom the obtained image in order to construct the cell lineage of thenematode. The so-called Nomarski microscope is used to obtain a cellimage. According to the Nomarski microscope, the external shape anddistribution of contents of a transparent subject are observed as lightand dark images. Biologically, a cell content (nucleus) and an externalshape (cell membrane), both transparent when using a common opticalmicroscope, can be observed as images of light and dark.

Conventionally, a plurality of image processing algorithms are used forextracting a nucleus area from an image taken by the Nomarskimicroscope. These image processing algorithms comprise an approach fordetecting an area, where the fine brightness variation in the image ispoor, as the nucleus, or an approach for extracting a portion, in whichthe change in the intensity is large in a wide range along the incidentangle of the light, as the nucleus. The former is exemplified by using afilter obtained by a combination of a Kirsch template type edgedetection operator with a moving average, or a filter binarizing theoutput of a Prewitt template type edge detection operator and applying adistance transform. For the latter, a filter for taking a difference ina sum of intensity value of a predetermined top and bottom pixel along aseeming angle of light is adopted.

However, the nucleus detection by these image processing algorithms isnot perfect, and therefore, an area recognized by any one of three typesof algorithms is determined as a nucleus area as a conclusion of a wholeimage processing system, which results in a complicated nucleusextraction operation.

In a cell image taken by the Nomarski microscope, a cytoplasmic portionis coarse in image quality, while a nucleus area is relatively smooth inimage quality. A method for extracting a smooth area as a nucleus froman image is studied using differences in image quality.

An object of the present invention is to efficiently extract a smooth orcoarse portion in image quality from an image.

Another object of the present invention is to provide a filter that iscapable of extracting a smooth or coarse portion in image quality froman image.

DISCLOSURE OF THE INVENTION

A filter of the present invention is characterized in that entropy of asmall section including a noted pixel (x, y) is calculated, and thenoted pixel (x, y) is renewed by an obtained entropy value.

Preferably, the filter is a filter in which a start point (x, y) isdetermined in an original image, the image is partitioned by a window ofsize (width, height)=(A, B) from the start point, entropy of thepartitioned window is calculated, and an obtained entropy value is savedon the coordinates (x, y) of a resulting image. In a desirable example,in a start point (x, y), x is ranged from 0 to (an original image widthminus A) and y is ranged from 0 to (an original image height minus B).

According to an area extracting method employed by the presentinvention, partitioning the image by a small window and scanning theimage with calculating entropy of the window facilitates the extractionof smooth portions from the image. The binarizing processing of thefiltered image yielded by the entropy filter with a threshold allowsgood extraction of the smooth portion from the image. In the presentspecification, “smooth” is defined as the difference in pixel valuesbeing relatively small, in other words, an intensity value of the pixelis relatively even. In contrast, “not smooth” is defined as thedifference in pixel values being relatively large, in other words, anintensity value of the pixel is relatively uneven. The intensity valuein a gray scale image is the value representing monochromic intensity.The intensity value in a color image is the value representing eachintensity of R, G, and B. Whether “the difference in pixel values issmall or large” in the color image is determined according to theproviso that, the closer the combination of R, G, and B, the smaller thedifference, while the more dissimilar the combination of R, G, and B,the larger the difference.

According to the present invention, it is easy to distinguish a smoothportion in image quality and a non-smooth portion (coarse in imagequality) from an image. The invention is not influenced by light anddark of the image. Therefore, the present invention effectively worksfor an image taken by an autoexposure type automatic photographingapparatus. In a widely used automatic photographing system by theNomarski microscope, an image is taken by the autoexposure camera sothat variances in light and dark are occurred depending on images. Thepresent invention is not influenced with the occasion. An image that isan object of the extracting method of the present invention can eitherbe an image in monochrome or color.

According to the present invention, a sensitivity of the entropy filtercan be varied at will by changing a window size. The entropy filter canbe operated in accordance with a situation where an object is a verysmall portion, or a situation where an object is a whole image. By doingthis, the entropy filter can conform to a situation where amagnification of microscope is changed. Also, the entropy filtereffectively works in a situation where a biological object changes.Specifically, in a situation where an image object is a living organism,a degree of coarseness of a cytoplasmic, and a degree of smoothness of anucleus area may vary depending upon variation of the biological object.However, it is possible to deal with the changes by selecting apreferred window size.

The use of the entropy filter of the present invention is not limited toextracting a smooth portion in image quality from an image. The entropyfilter may be applied for autofocus detection by utilizing the fact thatan image becomes blurred when the image is out of focus.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a view explaining an entropy filter;

FIG. 2 is a microscopic image of a cell;

FIG. 3 is a filterd image of the image shown in FIG. 2 processed by theentropy filter; and

FIG. 4 is a product of superimposing the resultant image followed bythreshold processing, on the microscopic image of FIG. 2.

PREFERRED MODE FOR CARRYING OUT THE INVENTION

An area extracting method of the present invention will be describedbased on a nucleus extraction from an image of a C. elegans early embryotaken using the Nomarski DIC microscope as a preferable example. FIG. 2is the microscopic image of a C. elegans early embryo in which thecytoplasmic portion (which is coarse in image quality) shows arelatively large difference in gray level, while the nucleus portion(which is relatively smooth in image quality) shows a relatively smalldifference in gray level.

The entropy filter employed by the present invention is a filter forefficient extraction of the smooth portion from the image. This employsthe property that the cytoplasmic portion is coarse in image quality,while, in contrast, the nucleus portion is relatively smooth in imagequality.

A left drawing of FIG. 1 shows a digital image data with a size of M×Npixels, an upper left is (0, 0) and a lower right is (M−1, N−1). A startpoint (x, y) is determined in the original image with a size of M×Npixels where x is ranged from 0 to (an image width minus a window width)and y is ranged from 0 to (an image height minus a window height).

Next, the image is partitioned by a window of size (width, height)=(A,B) from the noted pixel selected as the start point. Entropy of thepartitioned window is calculated and the obtained entropy value is savedon the coordinates (x, y) of a resulting image as a new pixel value. Inthe depicted drawing, x is in a range from 0 to (M minus one minus A),and y is in a range from 0 to (N minus one minus B).

Entropy is calculated based on the following equation (1).

$\begin{matrix}{\left( {{entropy}\mspace{14mu}{value}} \right) = {- {\sum\limits_{l = l_{\min}}^{l_{\max}}{{P(l)}\log\;{P(l)}}}}} & (1)\end{matrix}$

In equation (1), P(l) is a normalized intensity histogram produced byobtaining an intensity histogram H (1) for the image area whosecharacteristics to be measured (if an intensity level is L, 1=0, 1, 2, .. . , L−1), followed by dividing the frequency of each intensity levelby the total frequency (a pixel number of the image area), and thennormalizing to make the total pixel number 1.0. The nucleus area isdiscriminated from the cytoplasmic area by referring to the entropyvalue calculated using equation (1).

In the embodiment, the image is partitioned by a window of size (width,height)=(A, B) from the noted pixel selected as the start point andentropy of the partitioned window is calculated. However, the image maybe partitioned by a window of size (width, height)=(A, B) that containsa noted pixel (x, y) not in an upper left corner, and entropy of thepartitioned window may be calculated. In this case, the ranges of x andy of the noted pixel (x, y) differ from those in the figure. Forexample, the noted pixel (x, y) may be coordinates from (1, 1) to (Mminus A, N minus B).

The operation involving scanning the original image with calculatingentropy of a small section makes efficient extraction of the position ofthe nucleus possible. The entropy window size depends on the kind ofmicroscope and magnification used. A good result was obtained byscanning an image area window of 6 pixels×6 pixels to 20 pixels×20pixels, (preferably 10 pixels×10 pixels or 12 pixels×12 pixels). In thiscase, the pixel of the nucleus area ranges according to factors such ascell division from about 1000 pixels to 10000 pixels. The foregoingwindow size and number of pixels for the nucleus area are merely givenas examples.

FIG. 3 is a processed image of the cell image shown in FIG. 2 afterprocessing using the entropy filter. FIG. 4 is the product ofsuperimposing the resultant image of FIG. 3, which has been processed bythe entropy filter followed by threshold processing, on the microscopicimage of FIG. 2. In this way, a nucleus area that is smooth in imagequality is extracted from a cell image.

A preferred embodiment of the present invention is explained inconjunction with a nucleus extraction from an image of a C. elegansearly embryo taken by the Nomarski DIC microscope. However, the presentinvention is not limited to a nucleus extraction from a cell image. Anobject image is also not limited to an image taken by the Nomarskimicroscope but can be an image taken by other microscopes, and thepresent invention can even be applied to any image dealt with acomputer.

Automatic focus detection using the entropy filter will be explained.Automatic focus detection is generally obtained using contrast. However,in an image taken by the Nomarski microscope, the method using contrastdoes not work well. The entropy filter can be applied to automatic focusdetection by using the fact that an image becomes blurred when the imageis out of focus. This employs the property that an image becomes clearin proper focus (increase in entropy) while an image becomes smooth outof focus (decrease in entropy). When an object image (a cell image forexample) is always the same, determination as to whether an image isfocused can be anticipated according to variation range of an entropyvalue. A method of automatic focus detection is as follows. Firstly, anentropy value of an obtained image is calculated by gradually changing afocus. The window size is fixed at this time. Next, examine eachcalculated entropy value of one piece of image. Then, an image isdetermined as being in proper focus if a relatively large entropy valueis obtained.

INDUSTRIAL APPLICABILITY

The entropy filter can efficiently extract a smooth portion from animage without being influenced by brightness and darkness and/ormonochrome/color of an image. Preferably, the entropy filter can beapplied to a nucleus extraction from a cell and therefore applied to animage processing device of an automatic cell lineage construction systemof a C. elegans. The entropy filter can also be applied to autofocus ofphotograph.

1. A method of detecting a smooth area or coarse area in image qualityfrom an original image by processing the original image using an entropyfilter, said entropy filter comprising a computer and software embodiedon a computer-readable memory for implementation by the computer,comprising the steps of: providing the original image to the computer,each pixel of said image having an intensity and a location within theimage (x, y); calculating entropy of a small section of said image whoselocation in the image is derived from the location of a noted pixel (x,y) located within the small section to obtain an entropy value for saidpixel (x, y) and obtaining the entropy value for said each pixel of saidimage, wherein entropy is calculated based on the following equation(1): $\begin{matrix}{\left( {{entropy}\mspace{14mu}{value}} \right) = {- {\sum\limits_{l = l_{\min}}^{l_{\max}}{{P(l)}\log\;{P(l)}}}}} & (1)\end{matrix}$ where P(l) is a normalized intensity histogram obtained bydividing the frequency of each intensity level by the total number offrequencies, renewing the intensity of said each pixel of said image bythe entropy value, and binarizing said renewed intensity of said eachpixel using a threshold to obtain a binarized image including one ormore detected smooth areas or coarse areas.
 2. The method of claim 1,wherein said small section is defined by determining a start point (x,y) in said image, followed by partitioning said image with a window ofsize (width, height)=(A, B) from said start point, wherein entropy ofthe partitioned window is calculated, and an obtained entropy value issaved on the coordinates (x, y) of a resulting image, and wherein x isranged from 0 to (an image width minus a window width) and y is rangedfrom 0 to (an image height minus a window height).
 3. The method ofclaim 1, wherein the original image is a cell image and the smooth areais a nucleus, and wherein the nucleus is detected from the cell image.4. The method of claim 3, wherein the original image is taken by aNomarski microscope.
 5. A method of detecting a nucleus area from a cellimage by a computer, comprising: providing the cell image to thecomputer, each pixel of said cell image having an intensity and alocation within the image (x, y); calculating entropy of a small sectionof said image whose location in the image is derived from the locationof a noted pixel (x, y) located within the small section to obtain anentropy value for said pixel (x, y) and obtaining the entropy value forsaid each pixel of said image, wherein entropy is calculated based onthe following equation (1): $\begin{matrix}{\left( {{entropy}\mspace{14mu}{value}} \right) = {- {\sum\limits_{l = l_{\min}}^{l_{\max}}{{P(l)}\log\;{P(l)}}}}} & (1)\end{matrix}$ where P(l) is a normalized intensity histogram obtained bydividing the frequency of each intensity level by the total number offrequencies, renewing the intensity of said each pixel of said image bythe entropy value, and binarizing said renewed intensity of each pixelusing a threshold to obtain a binarized image including one or moredetected nucleus areas.
 6. The method of claim 5, wherein said smallsection is defined by determining a start point (x, y) in said image,followed by partitioning said image with a window of size (width,height)=(A, B) from said start point, wherein entropy of the partitionedwindow is calculated, and an obtained entropy value is saved on thecoordinates (x, y) of a resulting image, and wherein x is ranged from ato (an image width minus a window width) and y is
 7. The method of claim5, wherein the original image is taken by a Nomarski microscope.